Rtreemix (version 1.34.0)

distribution-methods: Method for generating the (scaled) probablility distribution induced with a given mutagenetic trees mixture model

Description

These functions generate the probability distribution induced with a given mutagenetic trees mixture model model on the space of all possible patterns of genetic events. The model has to be specified. The sampling mode and the parameters for the sampling times of the observed input and output probabilities are optional. The number of genetic events in the model cannot exceed 30.

Usage

distribution(model, sampling.mode, sampling.param, output.param)

Arguments

model

An RtreemixModel object that encodes a probability distribution on the set of all possible patterns.

sampling.mode

A character that specifies the sampling mode ("constant" or "exponential") for the observed input and output probabilities.

sampling.param

A numeric that specifies the sampling parameter for the observed input probabilities corresponding to the sampling mode given by sampling.mode.

output.param

A numeric that specifies the sampling parameter for the observed output probabilities corresponding to the sampling mode given by sampling.mode.

Value

The function returns a dataframe of all possible patterns with their corresponding probabilities derived from the specified trees mixture model. When the sampling mode and the sampling parameters (input and output) are specified their values are printed out.

References

Learning multiple evolutionary pathways from cross-sectional data, N. Beerenwinkel et al.

See Also

RtreemixModel-class, fit-methods

Examples

## Generate a random RtreemixModel object with 3 components.
mod <- generate(K = 3, no.events = 8, noise.tree = TRUE, prob = c(0.2, 0.8))
show(mod)

## See the probability distribution encoded by the model on the set of all possible patterns.
distr <- distribution(model = mod)
distr

## Get the probabilities.
distr$probability

## See the probability distribution encoded by the model on the set of all possible patterns
## calculated for given sampling mode, and corresponding input and output parameters.
distr1 <- distribution(model = mod, sampling.mode = "exponential", sampling.param = 1, output.param = 1)
distr1